1. Field of the Invention
The present invention relates to a method for locating a mobile telephone unit within a cellular service area, and more particularly to a method for estimating the location of a mobile unit based upon the probability of its being at a particular location of the service area given a certain set of observed attributes.
2. Description of the Related Art
A cellular telephone system must be able to locate a mobile unit within a cellular service area under various RF propagation conditions such, for example, when an E911 call is made from the mobile unit. Conventional methods for locating a mobile unit are typically based on either a triangulation technique which requires signals from three or more base stations within a designated service area, or an angle of arrival technique which requires at least two base stations. In many areas, the number of base stations the mobile unit can detect is less than two. Furthermore, both the triangulation and angle of arrival techniques inherently suffer from inaccuracies and signal fading which result from multi-path propagation.
In the above-noted related patent application, RF characteristics pertaining to one or more pilot signals radiated from a base station and specific to a particular location within the service area are detected by a mobile unit and transmitted back to a basestation where they are matched to a known set of RF characteristics and other information stored in a database located, for example, in a base station server. The database contains what is known in the art as attribute information and includes, for example, RF characteristics, e.g. pilot signal strength measurements indicative of power and phase-offset, time delay, angle of arrival and round-trip delay of pilot signals which differentiates one location from another. For convenience, the cellular service area is divided into a rectilinear grid and an exhaustive survey consisting of measurements of different attributes is carried out at each of the grid points (sub-cells) to identify the attribute values associated therewith. This information is stored in the database. It should be noted that collection of this information is an inherently time consuming and costly procedure.
The present invention is directed to a method of estimating, by a Bayesian probability computation procedure, the location of a mobile unit in the service area of a CDMA cellular telephone system and which, among other things, simplifies the generation of a database and eliminates the need for repeated attribute measurements at all of the grid points (sub-cells) in the cellular service area by using a model based approach.
In the present invention, for pilot signal strength or power measurements, a model for RF signal propagation which is used to characterize RF environments is first generated. The model is expressed in terms of a number of parameters such as total transmit power levels, pilot channel powers, antenna patterns and gains, antenna orientations, distance loss parameters, shadow fading parameters, etc. Some of these parameters are known to the service provider. Values of the other parameters are determined by carrying out pilot strength measurements along a few representative routes in the service area and adjusting the values of these parameters until they yield a good match between the pilot strength values predicted by the model and the corresponding measurements. In the case of a large and diverse service area, multiple models representing different parts of the sub-area may be needed. Once the optimal parameters have been determined, no more data needs to be collected. A database containing pilot signal visibility probabilities for each grid-point or sub-cell in the service area is next generated and stored in memory by running a simulation for all grid-points or sub-cells in the service area. Next, for the other attributes such as phase offsets, their behavior is characterized through a statistical model of the conditional probability of a mobile unit observing a specific phase-offset given that the mobile is located at a given sub-cell. This model is expressed in terms of a few parameters which, also, need to be determined through measurements. Once again, measurements at a few representative locations in the service area suffice for parameter estimation. Exhaustive measurements are not needed as in the referenced invention. The statistical model, moreover, is computationally straight forward, does not need a database, and can be generated in real time.
When pilot strength and phase offset measurements reported by a mobile unit are received by a location server, it uses these two models to determine the probability of the mobile units being at different grid-points within the service area given the measurements reported by it.
In the preferred method, an xe2x80x9ca-posteriorixe2x80x9d location probability distribution is used as an estimate of the mobile unit""s location. If the mobile unit reports multiple sets of measurements made at relatively small time intervals, the location server iteratively computes the location probability distribution. In this process, the xe2x80x9ca-posteriorixe2x80x9d distribution computed at the end of one step is used as the xe2x80x9ca-priorixe2x80x9d distribution for the next step. This procedure is referred to herein as the Bayesian-Update Location prediction Method (BLMP).